US20120203541A1 - Generating input suggestions - Google Patents

Generating input suggestions Download PDF

Info

Publication number
US20120203541A1
US20120203541A1 US13/143,069 US200913143069A US2012203541A1 US 20120203541 A1 US20120203541 A1 US 20120203541A1 US 200913143069 A US200913143069 A US 200913143069A US 2012203541 A1 US2012203541 A1 US 2012203541A1
Authority
US
United States
Prior art keywords
input
textual input
language
gram
textual
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Abandoned
Application number
US13/143,069
Other languages
English (en)
Inventor
Xun Liu
Guangqiang Zhang
Yufan Zhu
Zhengzhu Feng
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Google LLC
Original Assignee
Google LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Google LLC filed Critical Google LLC
Assigned to GOOGLE INC. reassignment GOOGLE INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: ZHANG, GUANGQIANG, FENG, ZHENGZHU, LIU, XUN, ZHU, YUFAN
Publication of US20120203541A1 publication Critical patent/US20120203541A1/en
Assigned to GOOGLE INC. reassignment GOOGLE INC. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: ZHU, YUFAN, ZHANG, GUANGQIANG, FENG, ZHENGZHU, LIU, XUN
Assigned to GOOGLE LLC reassignment GOOGLE LLC CHANGE OF NAME (SEE DOCUMENT FOR DETAILS). Assignors: GOOGLE INC.
Abandoned legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/02—Input arrangements using manually operated switches, e.g. using keyboards or dials
    • G06F3/023—Arrangements for converting discrete items of information into a coded form, e.g. arrangements for interpreting keyboard generated codes as alphanumeric codes, operand codes or instruction codes
    • G06F3/0233—Character input methods
    • G06F3/0236—Character input methods using selection techniques to select from displayed items
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/274—Converting codes to words; Guess-ahead of partial word inputs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01—Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/018—Input/output arrangements for oriental characters

Definitions

  • This specification relates to digital data processing, and in particular, to computer-implemented search services.
  • a conventional search engine can include a query input field that receives a textual input.
  • a conventional search service can provide search query suggestions for the textual input.
  • a user can select a search query suggestion for use as a search query.
  • a user may provide textual input that is represented in different input forms.
  • the textual input can include a mix of morphemes in a first script (e.g., Hanzi characters), lexical items in a second script (e.g., English words), and graphemes in the second script that represent phonetic representations of morphemes in the first script (e.g., Pinyin syllables, or Pinyin abbreviations).
  • This specification describes technologies relating to generation of search query suggestions.
  • one aspect of the subject matter described in this specification can be embodied in methods that include the actions of receiving a textual input entered in an input field by a user, the textual input including a first n-gram in a first form of representing a first language and at least one of: a second n-gram in a second form of representing the first language; and a third n-gram in a second language; generating one or more alternative representations of the textual input, where the alternative representations are in an ambiguous form that represents one or more input suggestions that do not directly match the textual input; sending the alternative representations to a suggestion service and receiving from the suggestion service one or more input suggestions; and comparing the one or more input suggestions to the textual input to identify a group of the one or more input suggestions as being selectable alternatives to the textual input for display in a user interface.
  • Other embodiments of this aspect include corresponding systems, apparatus, and computer program products.
  • Generating one or more alternative representations of the textual input in an ambiguous form includes: segmenting the textual input into one or more contiguous sequences of characters, where each sequence represents a word or query; identifying one or more representations of each segment, where each representation is in an alternative form; and replacing, in the textual input, one or more segments with an associated representation in an alternative form to produce an alternative representation of the textual input.
  • the textual input includes a second n-gram in a second form of representing the first language
  • generating one or more alternative representations of the textual input in the ambiguous form includes: generating a fourth n-gram from the textual input, where the fourth n-gram is an alternative representation of the textual input and includes one or more sequences of text in the second form.
  • the fourth n-gram includes one or more sequences of text in the first form.
  • the second form of representing the first language includes representing the first language using complete phonetic representations or partial phonetic representations.
  • the first language is Chinese
  • the first form of representing Chinese includes representing Chinese using Hanzi characters.
  • a complete phonetic representation is a Pinyin syllable
  • a partial phonetic representation is a Pinyin abbreviation.
  • the textual input includes a third n-gram in a second language and the second language is English.
  • the selectable alternatives include one or more input suggestions that are represented using Hanzi characters.
  • the textual input is received before the user submits the textual input in a request for a search and after waiting a predetermined amount of time after receiving each token of the textual input.
  • Automatically generating input suggestions from textual input represented in different input forms reduces how much user interaction is required to obtain search suggestions.
  • obtaining search suggestions for textual input represented in different forms can increase the coverage of searches by capturing search query suggestions that may not be convenient for a user to provide, e.g., the user may not have access to an input method editor (IME) or may not know how to provide textual input in a particular script of a language.
  • IME input method editor
  • Generating alternative representations, in an ambiguous form, of the textual input for use in determining the input suggestions reduces how much memory is required to store possible representations of a textual input.
  • generating alternative representations in an ambiguous form increases the precision, recall, and efficiency of identifying input suggestions (e.g., transliterations) by increasing the coverage of searches and reducing the number of input suggestions that are processed.
  • FIG. 1 is a block diagram illustrating an example of a flow of data in some implementations of a system that generates selectable alternatives textual input in different forms.
  • FIG. 2 is a block diagram illustrating an example input suggestion aggregator.
  • FIG. 3 is a diagram illustrating an example textual input and an example selectable alternative for the textual input.
  • FIG. 4 is a block diagram illustrating an example of a flow of data showing how input suggestions are generated from a particular textual input.
  • FIG. 5 is a flow chart showing an example process for automatically generating selectable alternatives of textual input in different forms.
  • FIG. 1 is a block diagram illustrating an example of a flow of data in some implementations of a system that generates selectable alternatives textual input in different forms.
  • a user 110 provides input 120 to a search engine query input field presented by a client 130 .
  • the input 120 includes n-grams in different forms.
  • An n-gram is a sequence of n consecutive tokens, e.g., characters or words.
  • An n-gram has an order, which is a number of tokens in the n-gram. For example, a 1-gram (or unigram) includes one token; a 2-gram (or bi-gram) includes two tokens.
  • the input 120 can include a first n-gram in a first form of representing a first language.
  • the input 120 can also include a second n-gram in a second form of representing the first language, or a third n-gram in a second language.
  • “ ” (e.g., “me” in English and pronounced “w ⁇ hacek over (o) ⁇ ”) can be a first n-gram in a first form of representing a first language, e.g., a Hanzi character for representing Chinese.
  • “wo” can be a second n-gram in a second form of representing the first language.
  • “wo” is a 2-gram that is a complete phonetic representation (e.g., a Pinyin syllable) of “ ”.
  • “w” is another example of a second n-gram in a second form of representing the first language.
  • “w” is a 1-gram that is a partial phonetic representation of multiple Hanzi characters, e.g., a Pinyin abbreviation of “ ” pronounced “w ⁇ hacek over (o) ⁇ ”, “ ” pronounced “w ⁇ ”, and “ ” pronounced “we ⁇ ”.
  • the Roman character “w” is referred to as a partial phonetic representation because it is the first character in the sequence of characters in a Pinyin syllable.
  • the client 130 sends to a search service 140 a request for selectable alternatives of the input 120 .
  • the request includes the input 120 .
  • the client 130 sends the request immediately after each token of a textual input, e.g., after each character of a first search query or each word of a first search query, is received at the search engine query input field.
  • selectable alternatives can be provided to the user as the user types each token of the textual input.
  • the client 130 implements a delay, waiting a predetermined amount of time before automatically making the request to the search service 140 .
  • a module 142 e.g., a software script, installed on the search service 140 receives the input 120 .
  • the module 142 processes the input 120 to transform the input 120 into an ambiguous form.
  • the module 142 generates one or more alternative representations of the input 120 that are each in an ambiguous form, as will be described in further detail below.
  • the module 142 sends the alternative representations to a suggestion service 144 that is installed on the search service 140 .
  • the search service 140 is installed on an intermediate server and the suggestion service 144 is installed on a receiving server that receives the alternative representations from the search service 140 .
  • the suggestion service 144 returns one or more input suggestions for the input 120 .
  • the input suggestions are alternatives to the input 120 , e.g., completions, transliterations.
  • the module 142 compares the one or more input suggestions to the input 120 to identify a group of the one or more input suggestions as being selectable alternatives to the input 120 .
  • the module 142 returns the selectable alternatives to the client 130 , in real time, i.e., as the user 122 is typing characters in the search engine query input field, for display in a user interface.
  • FIG. 2 is a block diagram illustrating an example input suggestion aggregator 200 .
  • the input suggestion aggregator 200 includes a transformation submodule 210 and a comparison submodule 220 .
  • the input suggestion aggregator 200 receives a textual input.
  • the transformation submodule 210 generates one or more alternative representations, in an ambiguous form, of the textual input.
  • the comparison submodule 220 receives the input suggestions, and compares the input suggestions to the textual input to identify a group of the one or more input suggestions as being selectable alternatives to the first textual input.
  • FIG. 3 is a diagram illustrating an example textual input and an example selectable alternative for the textual input.
  • the textual input includes the sequence of characters “ jingfd office hour”, which represent multiple n-grams in different forms.
  • the textual input includes a 1-gram in a first form of representing a first language, i.e., a Hanzi character “ ”.
  • the textual input also includes a 4-gram in a second form of representing the first language, i.e., a complete phonetic representation “j ⁇ ng” (a Pinyin syllable).
  • the textual input includes two 1-grams in a third form of representing the first language, i.e., a Pinyin abbreviation “f”, and a Pinyin abbreviation “d”.
  • the textual input also includes a 6-gram and a 4-gram in a different second language, i.e., the English words “office” and “hour”.
  • the selectable alternative includes the Hanzi characters “ ”, “ ”, “ ”, and “ ”.
  • the selectable alternative also includes the English words “office” and “hour”.
  • the Hanzi character “ ” is represented by a same character in the textual input.
  • the Hanzi character “ ” (e.g., “capital” in English and pronounced “j ⁇ ng”) is represented by the Pinyin syllable “j ⁇ ng” in the textual input.
  • the Hanzi character “ ” (e.g., “food” in English and pronounced “fan”) is represented by the Pinyin abbreviation “f” in the textual input, and the Hanzi character “ ” (e.g., “store” in English and pronounced “diàn”) is represented by the Pinyin abbreviation “d”.
  • the English words “office” and “hour” are represented by the same words in the textual input.
  • Example translations of the selectable alternative include “Beijing restaurant office hours” and “Beijing hotel office hours”, where “ ” is translated as “Beijing” and “ ” is translated as “restaurant” or “hotel”.
  • FIG. 4 is a block diagram illustrating an example of a flow of data showing how input suggestions are generated from a particular textual input.
  • the textual input includes the sequence of characters “ ggug”, where the Hanzi character “ ” can be translated alone as “middle” in English and pronounced “zh ⁇ ng”, or as “hit” in English and pronounced “zh ⁇ ng”.
  • the textual input includes a first 1-gram “ ”, a second 1-gram “g”, a third 1-gram “gu”, and a fourth 1-gram “g”.
  • Generating alternative representations in an ambiguous form includes segmenting the textual input into one or more contiguous sequences of characters.
  • the segmenting is performed using prefix matching.
  • the textual input is segmented into the contiguous sequences starting from a first character received as input from the user.
  • Each sequence of characters, starting from the first sequence at the beginning of the order in which sequences were segmented and ending at the last sequence at the end of the order, consists of the longest sequence of characters that represents a word or query.
  • a user provides as textual input a first character “X 1 ”, followed by a second character “X 2 ”, followed by a third character “X 3 ”, and followed by a fourth character “X 4 ”.
  • the textual input includes, from left to right, in the order in which each character was received, the characters “X 1 X 2 X 3 X 4 ”. If “X 1 X 2 X 3 X 4 ” represents a word, then the textual input is not segmented and only the contiguous sequence “X 1 X 2 X 3 X 4 ” is identified.
  • the transformation submodule 210 determines if “X 1 X 2 X 3 ” represents a word. If “X 1 X 2 X 3 ” represents a word, then the textual input is segmented into two contiguous sequences “X 1 X 2 X 3 ” and “X 4 ”.
  • the transformation submodule 210 determines if “X 1 X 2 ” represents a word. If “X 1 X 2 ” represents a word, then “X i X 2 ” is identified as a first contiguous sequence. Then, the transformation submodule 210 determines if “X 3 X 4 ” represents a word. If the sequence “X 3 X 4 ” represents a word, then the textual input is segmented into two contiguous sequences “X 1 X 2 ” and “X 3 X 4 ”.
  • “X 1 X 2 ” is identified as a first contiguous sequence.
  • a similar process is used to identify a second contiguous sequence in “X 2 X 3 X 4 ”.
  • the textual input is segmented into the two contiguous sequences “X 1 ” and “X 2 X 3 X 4 ”.
  • the transformation submodule 210 determines if “X 2 X 3 ” represents a word.
  • the segmenting is performed using midfix matching or postfix matching.
  • the sequence of characters “ ggug” is segmented into four contiguous sequences. “ ggug”, “ ggu”, “ gg”, and “ g” each do not represent a word, so “ ” is identified as a first contiguous sequence. “ggug”, “ggu”, and “gg” each do not represent a word, so “g” is identified as a second contiguous sequence.
  • “g” can be a prefix for a word in English (e.g., “good”, “grain”), or a Pinyin abbreviation (e.g., for the Pinyin syllables “gu”, “ga”, “gai”).
  • “gug” does not represent a word, but “gu” can represent a word, so “gu” is identified as a third contiguous sequence.
  • “gu” can represent a Pinyin syllable.
  • Example Pinyin syllables that “gu” can represent include: “g ⁇ hacek over (u) ⁇ ” (e.g., a phonetic representation of “ ”, which means “share” in English), “gù” (e.g., a phonetic representation of “ ”, which means “strong” in English), and “g ⁇ ” (e.g., a phonetic representation of “ ”, which means “lone” in English).
  • “gu” is identified as a third contiguous sequence and “g” (i.e., the last character received in “ ggug”) is identified as fourth contiguous sequence.
  • the textual input “ ggug” is segmented into four contiguous sequences “ ”, “g”, “gu”, and “g”.
  • Alternative representations, in generic forms, of the textual input are generated using the identified segments.
  • representations in alternative forms of each segment are identified.
  • each segment can be represented by a complete phonetic representation or a partial phonetic representation.
  • representations in alternative forms of “ ” include “zhong” (i.e., a Pinyin syllable) and “z” (i.e., a Pinyin abbreviation).
  • representations in alternative forms of “gu” include “g” (i.e., a Pinyin abbreviation).
  • representations in alternative forms of identified segments that consist of a single character are not identified.
  • representations, in alternative forms, of the second “g” and third “g” in the textual input are not identified.
  • Alternative representations of the textual input in an ambiguous form are generated from the identified segments and representations in alternative forms of the segments.
  • the segments in the textual input can be replaced in different combinations to generate the alternative representations.
  • examples of alternative representations include “zhongggug”, where “ ” was replaced by “zhong”; “zhongggg”, where “ ” was replaced by “zhong” and “gu” was replaced by “g”; “zggug”, where “ ” was replaced by “z”; “zggg”, where “ ” was replaced by “z” and “gu” was replaced by “g”; and “ ggg”, where “gu” was replaced by “g”.
  • FIG. 4 does not show all possible alternative representations in generic forms that are processed in practice.
  • the alternative representations can be referred to as being in an ambiguous form because the alternative representations can each represent one or more input suggestions.
  • the alternative representation “zggg” includes Pinyin abbreviations “z”, “g”, “g”, and “g”.
  • the first Pinyin abbreviation “z” in “zggg” can represent Pinyin syllables and Hanzi characters that do not correspond to “ ” in the textual input.
  • “z” can represent a Pinyin syllable “zi” that corresponds to the Hanzi characters “ ” and “ ”.
  • the second “g” in “zggg” can represent Pinyin syllables and Hanzi characters that do not match “gu” in the textual input.
  • “g” can represent a Pinyin syllable “gang” that corresponds to the Hanzi characters “ ” and “ ”.
  • the alternative representations are sent to a suggestion service.
  • the textual input is also sent to the suggestion service.
  • the suggestion service identifies one or more input suggestions using the alternative representations and returns the one or more input suggestions to the suggestion service.
  • examples of input suggestions include “ ” (e.g., “Google China” in English and pronounced “Zh ⁇ ng guó G ⁇ hacek over (u) ⁇ g ⁇ ”), “ ” (e.g., “Chinese national anthem” in English and pronounced “Zh ⁇ ng guó guó g ⁇ ”), and “ ” (e.g., “advertising industry” in English and pronounced “zuó gu ⁇ hacek over (a) ⁇ ng gào g ⁇ ng”).
  • FIG. 4 does not show all possible input suggestions that are processed in practice.
  • the comparison module 220 compares the input suggestions to the textual input to identify a group of the one or more input suggestions as being selectable alternatives to the first textual input. In particular, the comparison module 220 identifies input suggestions that are not likely to be represented by the textual input for exclusion from the group of the one or more input suggestions that are identified as being selectable alternatives to the first textual input.
  • a phonetic representation of “ ” is “zhong guo gu ge”
  • a phonetic representation of “ ” is “zhong guo guo ge”
  • a phonetic representation of “ ” is “zuo guang gao gong”, where diacritics have been removed.
  • the first segment “ ” (“zhong”) in the textual input is less likely to represent “ ” (“zuo”) than to represent “ ” (“zhong”).
  • the third segment “gu” is less likely to represent “ ” (“guo”) than to represent “ ” (“gu”), i.e., an identical match.
  • only direct matches are identified as being selectable alternatives to the textual input.
  • only “ ” (“zhong guo gu ge”) is a direct match, because the Hanzi character “ ” is a match of the Hanzi character “ ”, the Pinyin syllable “guo” is a match of the Pinyin abbreviation “g”, the Pinyin syllable “gu” is a match of the Pinyin syllable “gu”, and the Pinyin syllable “ge” is a match of the Pinyin abbreviation “g”.
  • the selectable alternatives are ranked according to frequencies that unique users have entered each selectable alternative as a query for a search.
  • the rankings are modified using edit distances.
  • selectable alternatives “women clothing” and “ ” e.g., “we” in English and pronounced “w ⁇ hacek over (o) ⁇ men”
  • the ranking of “women clothing” can be increased to indicate that it is more likely to be represented by the textual input, because “women clothing” includes the n-gram “women” that is identical to the textual input, and one or more operations are required to transform, e.g., transliterate, “ ” into “women”.
  • FIG. 5 is a flow chart showing an example process 500 for automatically generating selectable alternatives of textual input in different forms.
  • the process 500 includes receiving 510 a first textual input entered in an input field by a user.
  • the first textual input includes a first n-gram in a first form of representing a first language and at least one of: a second n-gram in a second form of representing the first language, and a third n-gram in a second language.
  • the process 500 also includes generating 520 one or more alternative representations of the first textual input, where the alternative representations are in an ambiguous form that represents one or more input suggestions that do not directly match the textual input.
  • the process 500 also includes sending 530 the alternative representations to a suggestion service and receiving from the suggestion service one or more input suggestions.
  • the process 500 also includes comparing 540 the one or more input suggestions to the first textual input to identify a group of the one or more input suggestions as being selectable alternatives to the first textual input for display in a user interface.
  • Embodiments of the subject matter and the functional operations described in this specification can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them.
  • Embodiments of the subject matter described in this specification can be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a tangible program carrier for execution by, or to control the operation of, data processing apparatus.
  • the tangible program carrier can be a computer-readable medium.
  • the computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, or a combination of one or more of them.
  • data processing apparatus encompasses all apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, or multiple processors or computers.
  • the apparatus can include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them.
  • a computer program also known as a program, software, software application, script, or code
  • a computer program does not necessarily correspond to a file in a file system.
  • a program can be stored in a portion of a file that holds other programs or data, e.g., one or more scripts stored in a markup language document, in a single file dedicated to the program in question, or in multiple coordinated files, e.g., files that store one or more modules, sub-programs, or portions of code.
  • a computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.
  • the processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output.
  • the processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application-specific integrated circuit).
  • processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer.
  • a processor will receive instructions and data from a read-only memory or a random access memory or both.
  • the essential elements of a computer are a processor for performing instructions and one or more memory devices for storing instructions and data.
  • a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks.
  • mass storage devices for storing data, e.g., magnetic, magneto-optical disks, or optical disks.
  • a computer need not have such devices.
  • a computer can be embedded in another device, e.g., a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, to name just a few.
  • PDA personal digital assistant
  • GPS Global Positioning System
  • Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices; magnetic disks, e.g., internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.
  • semiconductor memory devices e.g., EPROM, EEPROM, and flash memory devices
  • magnetic disks e.g., internal hard disks or removable disks
  • magneto-optical disks e.g., CD-ROM and DVD-ROM disks.
  • the processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
  • embodiments of the subject matter described in this specification can be implemented on a computer having a display device, e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor, for displaying information to the user and a keyboard and a pointing device, e.g., a mouse or a trackball, by which the user can provide input to the computer.
  • a display device e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor
  • keyboard and a pointing device e.g., a mouse or a trackball
  • Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback, e.g., visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input.
  • Embodiments of the subject matter described in this specification can be implemented in a computing system that includes a back-end component, e.g., as a data server, or that includes a middleware component, e.g., an application server, or that includes a front-end component, e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described is this specification, or any combination of one or more such back-end, middleware, or front-end components.
  • the components of the system can be interconnected by any form or medium of digital data communication, e.g., a communication network. Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), e.g., the Internet.
  • LAN local area network
  • WAN wide area network
  • the computing system can include clients and servers.
  • a client and server are generally remote from each other and typically interact through a communication network.
  • the relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Human Computer Interaction (AREA)
  • Health & Medical Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Audiology, Speech & Language Pathology (AREA)
  • Computational Linguistics (AREA)
  • General Health & Medical Sciences (AREA)
  • Machine Translation (AREA)
  • Document Processing Apparatus (AREA)
US13/143,069 2009-10-29 2009-11-25 Generating input suggestions Abandoned US20120203541A1 (en)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
PCT/CN2009/001205 WO2011050494A1 (en) 2009-10-29 2009-10-29 Generating input suggestions
CNPCT/CN2009/001205 2009-10-29
PCT/CN2009/001317 WO2011050501A1 (en) 2009-10-29 2009-11-25 Generating input suggestions

Publications (1)

Publication Number Publication Date
US20120203541A1 true US20120203541A1 (en) 2012-08-09

Family

ID=43921229

Family Applications (1)

Application Number Title Priority Date Filing Date
US13/143,069 Abandoned US20120203541A1 (en) 2009-10-29 2009-11-25 Generating input suggestions

Country Status (4)

Country Link
US (1) US20120203541A1 (ko)
JP (1) JP2013509623A (ko)
KR (1) KR20120095914A (ko)
WO (2) WO2011050494A1 (ko)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130096918A1 (en) * 2011-10-12 2013-04-18 Fujitsu Limited Recognizing device, computer-readable recording medium, recognizing method, generating device, and generating method
US20130289973A1 (en) * 2012-04-30 2013-10-31 Google Inc. Techniques for assisting a user in the textual input of names of entities to a user device in multiple different languages
US20150121290A1 (en) * 2012-06-29 2015-04-30 Microsoft Corporation Semantic Lexicon-Based Input Method Editor
US11227608B2 (en) * 2020-01-23 2022-01-18 Samsung Electronics Co., Ltd. Electronic device and control method thereof
US11263399B2 (en) * 2017-07-31 2022-03-01 Apple Inc. Correcting input based on user context

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050044495A1 (en) * 1999-11-05 2005-02-24 Microsoft Corporation Language input architecture for converting one text form to another text form with tolerance to spelling typographical and conversion errors
US20050222838A1 (en) * 2004-03-23 2005-10-06 Gong Xue S Chinese romanization
US7107204B1 (en) * 2000-04-24 2006-09-12 Microsoft Corporation Computer-aided writing system and method with cross-language writing wizard

Family Cites Families (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09128376A (ja) * 1995-10-30 1997-05-16 Sharp Corp 中国語文書処理装置
JPH1011447A (ja) * 1996-06-21 1998-01-16 Ibm Japan Ltd パターンに基づく翻訳方法及び翻訳システム
US6351726B1 (en) * 1996-12-02 2002-02-26 Microsoft Corporation Method and system for unambiguously inputting multi-byte characters into a computer from a braille input device
US7165019B1 (en) * 1999-11-05 2007-01-16 Microsoft Corporation Language input architecture for converting one text form to another text form with modeless entry
JP2001229155A (ja) * 2000-02-14 2001-08-24 Toshiba Corp 中国語入力変換処理装置、中国語入力変換処理方法及び記録媒体
JP2002312354A (ja) * 2001-04-09 2002-10-25 Omron Corp ピンインの入力方法およびこの方法を用いた情報処理装置ならびに中国語入力用のプログラム
US8010523B2 (en) * 2005-12-30 2011-08-30 Google Inc. Dynamic search box for web browser
US8332207B2 (en) * 2007-03-26 2012-12-11 Google Inc. Large language models in machine translation
CN101206673A (zh) * 2007-12-25 2008-06-25 北京科文书业信息技术有限公司 网络搜索过程中关键词的智能纠错系统及方法
CN101493727A (zh) * 2008-01-22 2009-07-29 刘啸旻 语句输入法的自然分词和混合输入
CN101566882A (zh) * 2009-06-02 2009-10-28 腾讯科技（深圳）有限公司 文字输入系统及文字输入方法

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050044495A1 (en) * 1999-11-05 2005-02-24 Microsoft Corporation Language input architecture for converting one text form to another text form with tolerance to spelling typographical and conversion errors
US7107204B1 (en) * 2000-04-24 2006-09-12 Microsoft Corporation Computer-aided writing system and method with cross-language writing wizard
US20050222838A1 (en) * 2004-03-23 2005-10-06 Gong Xue S Chinese romanization

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130096918A1 (en) * 2011-10-12 2013-04-18 Fujitsu Limited Recognizing device, computer-readable recording medium, recognizing method, generating device, and generating method
US9082404B2 (en) * 2011-10-12 2015-07-14 Fujitsu Limited Recognizing device, computer-readable recording medium, recognizing method, generating device, and generating method
US20130289973A1 (en) * 2012-04-30 2013-10-31 Google Inc. Techniques for assisting a user in the textual input of names of entities to a user device in multiple different languages
US8818791B2 (en) * 2012-04-30 2014-08-26 Google Inc. Techniques for assisting a user in the textual input of names of entities to a user device in multiple different languages
US20140365204A1 (en) * 2012-04-30 2014-12-11 Google Inc. Techniques for assisting a user in the textual input of names of entities to a user device in multiple different languages
US9442902B2 (en) * 2012-04-30 2016-09-13 Google Inc. Techniques for assisting a user in the textual input of names of entities to a user device in multiple different languages
US20150121290A1 (en) * 2012-06-29 2015-04-30 Microsoft Corporation Semantic Lexicon-Based Input Method Editor
US9959340B2 (en) * 2012-06-29 2018-05-01 Microsoft Technology Licensing, Llc Semantic lexicon-based input method editor
US11263399B2 (en) * 2017-07-31 2022-03-01 Apple Inc. Correcting input based on user context
US20220366137A1 (en) * 2017-07-31 2022-11-17 Apple Inc. Correcting input based on user context
US11900057B2 (en) * 2017-07-31 2024-02-13 Apple Inc. Correcting input based on user context
US11227608B2 (en) * 2020-01-23 2022-01-18 Samsung Electronics Co., Ltd. Electronic device and control method thereof

Also Published As

Publication number Publication date
WO2011050501A1 (en) 2011-05-05
WO2011050494A1 (en) 2011-05-05
JP2013509623A (ja) 2013-03-14
KR20120095914A (ko) 2012-08-29

Similar Documents

Publication Publication Date Title
US11514035B1 (en) Query refinements using search data
US8630847B2 (en) Word probability determination
US8046222B2 (en) Segmenting words using scaled probabilities
US8386237B2 (en) Automatic correction of user input based on dictionary
KR101850124B1 (ko) 교차-언어 쿼리 제안을 위한 쿼리 번역 평가
US9465797B2 (en) Translating text using a bridge language
US8521761B2 (en) Transliteration for query expansion
US8688727B1 (en) Generating query refinements
JP5264892B2 (ja) 多言語情報検索
US8745051B2 (en) Resource locator suggestions from input character sequence
TWI454943B (zh) 一電腦實施方法及一用於自動搜尋條件校正之系統
CN107092615B (zh) 来自文档的查询建议
US20120330989A1 (en) Detecting source languages of search queries
US20090055168A1 (en) Word Detection
US20120330919A1 (en) Determining cross-language query suggestion based on query translations
US20120203541A1 (en) Generating input suggestions
US20140379680A1 (en) Generating search query suggestions
WO2012052794A1 (en) Universal search engine interface and application

Legal Events

Date Code Title Description
AS Assignment

Owner name: GOOGLE INC., CALIFORNIA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:LIU, XUN;ZHANG, GUANGQIANG;ZHU, YUFAN;AND OTHERS;SIGNING DATES FROM 20100311 TO 20100312;REEL/FRAME:024124/0731

AS Assignment

Owner name: GOOGLE INC., CALIFORNIA

Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:LIU, XUN;ZHANG, GUANGQIANG;ZHU, YUFAN;AND OTHERS;SIGNING DATES FROM 20100209 TO 20100301;REEL/FRAME:029121/0386

STCB Information on status: application discontinuation

Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION

AS Assignment

Owner name: GOOGLE LLC, CALIFORNIA

Free format text: CHANGE OF NAME;ASSIGNOR:GOOGLE INC.;REEL/FRAME:044142/0357

Effective date: 20170929